 IntroductionS. Lakshmivarahan
Chapter Chapter 1 in Learning Algorithms Theory and Applications, 1981, pp 1-18 from Springer Abstract: Abstract Learning has been the interest of psychologists and mathematicians for decades and more recently, of engineers and computer-scientists. The interest of a psychologist or a mathematician in learning is to explain or describe the way in which animals learn to do a variety of skills by observing the changes in their behavior. Such an approach may be termed as the descriptive approach. A wide range of mathematical models have been developed for this purpose. The work by Bush and Mosteller [B10], Luce [L14] Hilgard [H4], Norman [N10], Iosifescu and Theodorescu [12] to mention a few, belong to this category. On the contrary, in systems theory and computer science the aim is to develop a computer program or build a machine, perhaps in the context of pattern recognition or artificial intelligence, which will learn to perform certain prespecified tasks such as to play games or classify a class of x-ray pictures and diagnose disease, etc. Fu [F4] [F5] [F6], Tsypkin [T4] [T5], Sklansky [S9], Mendel [M6 [M7], Saridis [S4], Nilsson [N9], Csibi [C10] Slagle [S10], Fukunaga [F8]. Such an approach is often called the prescriptive approach to learning. Date: 1981 There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4612-5975-6_1 Ordering information: This item can be ordered from DOI: 10.1007/978-1-4612-5975-6_1 Access Statistics for this chapter More chapters in Springer Books from Springer |
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